The biological heterogeneity of oestrogen receptor positive breast cancer and its phenotypic characterisation

Although global gene microarray studies have demonstrated the molecular heterogeneity of breast cancer (BC) and provided potential for clinical applications, the molecular subclassification of luminal/ER-positive tumours, which is the largest class of BC, remains unclear. Characterisation of luminal/ER-positive subtypes could have important implications in clinical decision-making and patient management. The patient study cohort is derived from a consecutive series of approximately 1902 cases of primary operable invasive breast carcinoma obtained from the Nottingham Tenovus Primary Breast Carcinoma Series, with patients presenting between 1986 and 1998. This is a well-characterized series of primary breast carcinoma that has been treated in a uniform way and previously used to study a wide range of proteins. Using gene microarray experiments in 128 frozen invasive BC derived from this series , 47,2 93 gene transcripts were analysed using a number of different bio-statistical models to identify a transcript signature for luminal/ER-positive BC, from which candidate genes were selected and that can be used to characterise ER-positive breast cancer. In addition, other biomarkers with strong relevance in ER-positive breast cancer were studied because the evidence strongly suggests an important role in the biology and molecular classification of ER-positive breast cancer. The selection criteria was based on published literature concentrating mainly on ER related pathways including ER coregulators (CARMI, PELPI), cellular proliferation (p27. TK1, cyclin B1), apoptosis (Bc12), Akt/PIK3 pathway (FOX03a), gene expression profiling (FOXA1, XBP1, TFF1) and endocrine resistance (CD71). Immunohistochemistry and high throughput tissue micro array technology were used to study the protein expression of 16 biomarkers with strong relevance to ER pathways in a well characterised consecutive series of invasive BC (n=1902) in addition to anther 9 markers that were available from the database of the breast cancer research group, University of Nottingham. The data were analysed using different clustering methods including K-means and Partitioning around Medoids. Kaplan Meier plots with Log-rank test (LR) were used to model clinical outcome. A transcript signature for ER positive BC was identified including RERG, GATA3 and other genes by a supervised classification analysis using 10-fold external cross-validation of the gene microarray data. Immunohistochemical validation studies confirmed their association with ER positive BC. Through a consensus approach using different clustering techniques applied to protein expression data 25 markers, three biological clusters (patient subclasses) in ER positive breast cancer showing significant difference in clinical outcome (LR= 28.185 & p<0.001) have been identified. Importantly, the poor prognosis cluster was significantly characterised by high tumour grade and frequent development of distant metastasis. In conclusion, our results emphasised the heterogeneity of luminal/ER-positive BC. Molecular profiling of breast cancer using protein biomarkers on TMAs can sub-classify ER-positive tumours into clinically and biologically relevant subgroups

The biological heterogeneity of oestrogen receptor positive breast cancer and its phenotypic characterisation

Although global gene microarray studies have demonstrated the molecular heterogeneity of breast cancer (BC) and provided potential for clinical applications, the molecular subclassification of luminal/ER-positive tumours, which is the largest class of BC, remains unclear. Characterisation of luminal/ER-positive subtypes could have important implications in clinical decision-making and patient management. The patient study cohort is derived from a consecutive series of approximately 1902 cases of primary operable invasive breast carcinoma obtained from the Nottingham Tenovus Primary Breast Carcinoma Series, with patients presenting between 1986 and 1998. This is a well-characterized series of primary breast carcinoma that has been treated in a uniform way and previously used to study a wide range of proteins. Using gene microarray experiments in 128 frozen invasive BC derived from this series , 47,2 93 gene transcripts were analysed using a number of different bio-statistical models to identify a transcript signature for luminal/ER-positive BC, from which candidate genes were selected and that can be used to characterise ER-positive breast cancer. In addition, other biomarkers with strong relevance in ER-positive breast cancer were studied because the evidence strongly suggests an important role in the biology and molecular classification of ER-positive breast cancer. The selection criteria was based on published literature concentrating mainly on ER related pathways including ER coregulators (CARMI, PELPI), cellular proliferation (p27. TK1, cyclin B1), apoptosis (Bc12), Akt/PIK3 pathway (FOX03a), gene expression profiling (FOXA1, XBP1, TFF1) and endocrine resistance (CD71). Immunohistochemistry and high throughput tissue micro array technology were used to study the protein expression of 16 biomarkers with strong relevance to ER pathways in a well characterised consecutive series of invasive BC (n=1902) in addition to anther 9 markers that were available from the database of the breast cancer research group, University of Nottingham. The data were analysed using different clustering methods including K-means and Partitioning around Medoids. Kaplan Meier plots with Log-rank test (LR) were used to model clinical outcome. A transcript signature for ER positive BC was identified including RERG, GATA3 and other genes by a supervised classification analysis using 10-fold external cross-validation of the gene microarray data. Immunohistochemical validation studies confirmed their association with ER positive BC. Through a consensus approach using different clustering techniques applied to protein expression data 25 markers, three biological clusters (patient subclasses) in ER positive breast cancer showing significant difference in clinical outcome (LR= 28.185 & p<0.001) have been identified. Importantly, the poor prognosis cluster was significantly characterised by high tumour grade and frequent development of distant metastasis. In conclusion, our results emphasised the heterogeneity of luminal/ER-positive BC. Molecular profiling of breast cancer using protein biomarkers on TMAs can sub-classify ER-positive tumours into clinically and biologically relevant subgroups

The biological heterogeneity of oestrogen receptor positive breast cancer and its phenotypic characterisation

Although global gene microarray studies have demonstrated the molecular heterogeneity of breast cancer (BC) and provided potential for clinical applications, the molecular subclassification of luminal/ER-positive tumours, which is the largest class of BC, remains unclear. Characterisation of luminal/ER-positive subtypes could have important implications in clinical decision-making and patient management. The patient study cohort is derived from a consecutive series of approximately 1902 cases of primary operable invasive breast carcinoma obtained from the Nottingham Tenovus Primary Breast Carcinoma Series, with patients presenting between 1986 and 1998. This is a well-characterized series of primary breast carcinoma that has been treated in a uniform way and previously used to study a wide range of proteins. Using gene microarray experiments in 128 frozen invasive BC derived from this series, 47,293 gene transcripts were analysed using a number of different bio-statistical models to identify a transcript signature for luminal/ER-positive BC, from which candidate genes were selected and that can be used to characterise ER-positive breast cancer. In addition, other biomarkers with strong relevance in ER- positive breast cancer were studied because the evidence strongly suggests an important role in the biology and molecular classification of ER-positive breast cancer. The selection criteria was based on published literature concentrating mainly on ER related pathways including ER coregulators (CARM1, PELP1), cellular proliferation (p27, TK1, cyclin B1), apoptosis (Bcl2), AktIPIK3 pathway (FOX03a), gene expression profiling (FOXA1, XBP1, TFF1) and endocrine resistance (CD71). Immunohistochemistry and high throughput tissue microarray technology were used to study the protein expression of 16 biomarkers with strong relevance to ER pathways in a well characterised consecutive series of invasive BC (n=1902) in addition to anther 9 markers that were available from the database of the breast cancer research group, University of Nottingham. The data were analysed using different clustering methods including K-means and Partitioning around Medoids. Kaplan Meier plots with Log-rank test (LR) were used to model clinical outcome. A transcript signature for ER positive BC was identified including RERG, GATA3 and other genes by a supervised classification analysis using 10-fold external cross-validation of the gene microarray data. Immunohistochemical validation studies confirmed their association with ER positive BC. Through a consensus approach using different clustering techniques applied to protein expression data 25 markers, three biological clusters (patient subclasses) in ER positive breast cancer showing significant difference in clinical outcome (LR= 28.185 & p<0.001) have been identified. Importantly, the poor prognosis cluster was significantly characterised by high tumour grade and frequent development of distant metastasis. In conclusion, our results emphasised the heterogeneity of luminal/ER-positive BC. Molecular profiling of breast cancer using protein biomarkers on TMAs can sub-classify ER-positive tumours into clinically and biologically relevant subgroups.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Transferrin receptor (CD71) is a marker of poor prognosis in breast cancer and can predict response to tamoxifen

Transferrin receptor (CD71) is involved in the cellular uptake of iron and is expressed on cells with high proliferation. It may be implicated in promoting the growth of endocrine resistant phenotypes within ER+/luminal-like breast cancer. We used a panel of in vitro cell models of acquired resistance to tamoxifen (TAMR), Faslodex (FASR) or severe oestrogen deprivation (MCF-7X) and the ER+ luminal MCF-7 parental line to determine CD71 mRNA expression and to study transferrin (Tf) effects on in vitro tumour growth and its inhibition. Furthermore, CD71 protein expression was assessed in a well-characterized series of patients with invasive breast carcinoma using tissue microarrays. Our results demonstrated a striking elevation of CD71 in all cell models of acquired resistance. Exogenous Tf significantly promoted growth in MCF-7-X and MCF-7 cells but more so in MCF-7-X; this growth was significantly reduced by Faslodex (FAS) or a phosphoinositide-3 kinase inhibitor (LY294002). Increased CD71 expression was associated with poor NPI score, tumour proliferation, basal CKs, p53, EGFR, HER2, steroid receptor negativity and shortened breast cancer specific survival (P < 0.001). On multivariate analysis, CD71 was found to be an independent prognostic factor in the ER+ cohort of patients. In conclusion, therapies of current interest in breast cancer (e.g. FAS, PI3K-inhibitors) appear able to partially impact on transferrin/CD71-promoted growth, but further investigation of this important mitogenic mechanism may assist in designing new therapeutic strategies to target highly proliferative, endocrine resistant breast cancers. CD71 appears to be a candidate marker of a subgroup of ER+/luminal-like breast cancer characterised by poor outcome and resistance to tamoxifen